Fundamentals of Machine Learning

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Department of Instrumentation and Control Engineering

Synopsis:

The course is aimed at introducing students to the basics of machine learning and solving basic problems regression, classification, cluster analysis. It includes an explanation of basic machine learning algorithms, the basics of working with data and the basics of data analysis.

Requirements:

Syllabus of lectures:

1. Machine learning - introduction to the issue, basic concepts and tools in the field of machine learning, ethical principles in machine learning

2. Input data, formats, data structures, data life cycle in machine learning, basic methods of data selection and preprocessing

3. State space - creation and basic search methods

4. Regression - task definition and basic algorithms

5. Classification - task definition and basic algorithms

6. Cluster analysis - task definition and basic algorithms

7. Anomaly detection

Syllabus of tutorials:

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No time-table has been prepared for this course

The course is a part of the following study plans: